关键词: G-protein-coupled receptor Markov state model cannabinoid receptor 1 molecular dynamics transition-based reweighting analysis method umbrella sampling variational autoencoder well-tempered metadynamics

来  源:   DOI:10.1101/2023.09.29.560261   PDF(Pubmed)

Abstract:
New psychoactive substances (NPS) targeting cannabinoid receptor 1 pose a significant threat to society as recreational abusive drugs that have pronounced physiological side effects. These greater adverse effects compared to classical cannabinoids have been linked to the higher downstream β-arrestin signaling. Thus, understanding the mechanism of differential signaling will reveal important structure-activity relationship essential for identifying and potentially regulating NPS molecules. In this study, we simulate the slow (un)binding process of NPS MDMB-Fubinaca and classical cannabinoid HU-210 from CB1 using multi-ensemble simulation to decipher the effects of ligand binding dynamics on downstream signaling. The transition-based reweighing method is used for the estimation of transition rates and underlying thermodynamics of (un)binding processes of ligands with nanomolar affinities. Our analyses reveal major interaction differences with transmembrane TM7 between NPS and classical cannabinoids. A variational autoencoder-based approach, neural relational inference (NRI), is applied to assess the allosteric effects on intracellular regions attributable to variations in binding pocket interactions. NRI analysis indicate a heightened level of allosteric control of NPxxY motif for NPS-bound receptors, which contributes to the higher probability of formation of a crucial triad interaction (Y7.53-Y5.58-T3.46) necessary for stronger β-arrestin signaling. Hence, in this work, MD simulation, data-driven statistical methods, and deep learning point out the structural basis for the heightened physiological side effects associated with NPS, contributing to efforts aimed at mitigating their public health impact.
摘要:
针对大麻素受体1(CB1)的新型精神活性物质(NPS)作为娱乐性滥用药物对社会构成了重大威胁,可以避免发现并具有较高的生理副作用。NPS的这些生理副作用显示与更高的β-抑制蛋白信号传导有关。我们假设NPxxY基序的构象动力学差异导致与经典大麻素相反的NPS的不同下游信号传导。为了比较NPS和经典大麻素结合对NPxxY构象集合的动态影响,我们使用无偏和有偏分子动力学模拟,模拟了来自CB1的NPSMDMB-Fubinaca和经典大麻素HU-210的(非)结合过程。基于过渡的重重方法(TRAM)用于结合多集合模拟,以估算具有纳摩尔亲和力的配体(非)结合过程的过渡速率和基本热力学,在那里获得局部可逆采样更昂贵。我们的分析表明,配体使用相同的途径但通过不同的机制与受体解除结合。进一步的分析揭示了NPS结合CB1的NPxxY基序中更高的构象波动,支持我们的假设。使用基于神经理性推理的变分自动编码器(VAE)进一步验证了观察结果,对于NPS结合的CB1,其显示结合袋残基与NPxxY之间的基于动态变构的相互作用更高。因此,在这项工作中,MD模拟,数据驱动的统计方法,和深度学习指出NPS和经典大麻素的(非)结合和下游信号传导存在显著差异。
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